On the roles of different foreign currencies in European ... · on contrasting foreign currency use...

On the roles of different foreign currencies in European bank lending Signe Krogstrup and Cédric Tille

SNB Working Papers 7/2016

Disclaimer The views expressed in this paper are those of the author(s) and do not necessarily represent those of the Swiss National Bank. Working Papers describe research in progress. Their aim is to elicit comments and to further debate. copyright© The Swiss National Bank (SNB) respects all third-party rights, in particular rights relating to works protected by copyright (infor-mation or data, wordings and depictions, to the extent that these are of an individual character). SNB publications containing a reference to a copyright (© Swiss National Bank/SNB, Zurich/year, or similar) may, under copyright law, only be used (reproduced, used via the internet, etc.) for non-commercial purposes and provided that the source is mentioned. Their use for commercial purposes is only permitted with the prior express consent of the SNB. General information and data published without reference to a copyright may be used without mentioning the source. To the extent that the information and data clearly derive from outside sources, the users of such information and data are obliged to respect any existing copyrights and to obtain the right of use from the relevant outside source themselves. limitation of liability The SNB accepts no responsibility for any information it provides. Under no circumstances will it accept any liability for losses or damage which may result from the use of such information. This limitation of liability applies, in particular, to the topicality, accu−racy, validity and availability of the information. ISSN 1660-7716 (printed version) ISSN 1660-7724 (online version) © 2016 by Swiss National Bank, Börsenstrasse 15, P.O. Box, CH-8022 Zurich

Legal Issues

1

On the roles of different foreign currencies inEuropean bank lending

Signe Krogstrup

Swiss National Bank

[email protected]

and

Cedric Tille

The Graduate Institute of International and Development Studies

[email protected]

May 2, 2016

Abstract

We draw on a new data set on the use of Swiss francs and other currencies by European

banks to assess the patterns of foreign currency bank lending. We show that the patterns

differ sharply across foreign currencies. The Swiss franc is used predominantly for lending

to residents, especially households. It is sensitive to the interest rate differential, exchange

rate developments, funding availability, and to some extent international trade. Domestic

lending in other currencies is used, to a greater extent, in cross-border lending, and for

lending to resident nonfinancial firms, and is much less sensitive to the drivers identified

for Swiss franc lending. Policy measures aimed at foreign currency lending have a clear

impact on lending to residents. The results underline that not all foreign currencies are

alike when it comes to foreign currency bank lending and the associated financial stability

risks.

JEL Classification: F32, F34, F36.

Keywords: Swiss franc lending, foreign currency lending, cross-border transmission of shocks,

European bank balance sheets.

We are grateful to Jin Cao, Yin-Wong Cheung, Linda Goldberg, Frank Westermann, participants at an SNBbrownbag and participants at the Workshop on International Currency Exposure, held at the CESIFO - VeniceInternational University 2015 Venice Summer Institute for valuable comments. The views in this paper aresolely the responsibility of the authors and do not necessarily reflect the views of the Swiss National Bank.

2

1 Introduction

Prior to the crisis, banks in emerging Europe increased the share of their business in foreign

currencies. As an example, 39 percent of the assets of Hungarian banks and 40 percent of

their liabilities were denominated in foreign currencies in 2007. By 2009 these shares had

risen to 52 and 54 percent, respectively. The global crisis then led to a reassessment of banks

international activities across borders and in foreign currencies, and by the end of 2014 the

shares of Hungarian banks assets and liabilities that were not in forint had fallen back to 36

and 32 percent.

Bank lending in foreign currencies is of concern to policy makers as it may disrupt fi-

nancial stability. Household mortgages in foreign currencies is a case in point. While these

can have the appeal of low interest rates, they leave households exposed to the fluctuations

of exchange rates, which are not always understood by the borrower ex ante. Unexpected

appreciations can lead to sharp increases in monthly payments, and the associated deterio-

ration in borrowers financial situation can in turn weaken the banking sector and systemic

concerns (Yesin [2013]). A large literature examines the issue of foreign currency activity of

banks to better understand the drivers of banks’ use of foreign currencies in lending and the

associated risks. The literature shows that banks’ activities in foreign currencies can bring

benefits that need to be weighted against the cost of exchange rate exposure. This balancing

exercise is complex, and takes place in the context of the globalized nature of the banking

industry, which by itself makes banks a potent channel of international transmission of eco-

nomic fluctuations (Cetorelli and Goldberg [2011]). The previous literature, however, focuses

on contrasting foreign currency use with local currency use, but treats all foreign currencies

alike, as homogeneous. In this paper, we contribute to this literature by broadening the scope

of investigated foreign currencies. Drawing on a new dataset on banks’ balances sheet in

different currencies, we show that banks’ lending in Swiss francs takes different forms, and is

impacted by different factors, than lending in other foreign currencies. That different foreign

currencies have different implications for lending dynamics and financial stability may matter

for how to best approach the design of policies to counter the associated risks.

Our analysis is based on the Swiss franc lending monitor, a novel dataset collected by

the Swiss National Bank in cooperation with other European central banks. It provides

information of the currency composition of the banking sector’s balance sheet for a broad

range of European countries. The stylized facts on bank lending in the different currencies

suggest substantial heterogeneity across currencies. In particular, the Swiss franc is used

primarily for lending to local households, while other foreign currency lending is to a higher

degree used for lending to non-financial companies and cross border lending. Moreover, and

in line with findings in Yesin [2013] based on the same dataset, we confirm that banks only

partially offset their on-balance sheet Swiss franc position through liabilities denominated in

Swiss francs. In contrast, other foreign currency lending is associated with much less balance

1

3

sheet currency mismatch.

We further undertake an econometric analysis to assess which macroeconomic variables

drive bank lending in the different currencies, and document a substantial extent of hetero-

geneity across country groups as well as across currencies. Specifically, Swiss franc lending to

domestic residents is sensitive to funding costs, exchange rate developments, funding availabil-

ity, and (to some extent) international trade flows. Lending in other foreign currencies shows

much less sensitivity to these variables. The results thus suggest that lumping all foreign cur-

rency lending together when assessing the drivers of this lending may mask important cross

currency heterogeneity in these drivers. We also find that policy measures aimed at curb-

ing lending in specific currencies matter, and base this finding on the specific restrictions on

Swiss franc lending adopted by Hungary in late 2011 and early 2012. These reduced lending

in Swiss francs to residents. The effects were partially offset through higher lending in euros,

however, suggesting that macroprudential measures targeting the use of specific currencies

considered risky may have the effect of migrating the risk to other currencies.

The rest of the paper is structured as follows. Section 2 reviews the related literature.

Section 3 presents the Swiss lending monitor data and some major stylized facts. The econo-

metric analysis is undertaken in section 4, which presents the explanatory variables and the

regression findings. Section 5 concludes and the appendix describes the data.

2 Related Literature

Our work ties to several broad streams of literature. The first is the study of foreign currency

lending and deposits. Contributions have focused on the drivers of foreign currency lending.

For instance, Brown and Haas [2012] consider the role of foreign banks in issuing foreign

currency lending. One of their findings is a link between the two sides of the balance sheet,

as that movements in foreign currency deposits are transmitted to foreign currency lending.

Other papers consider banks’ liabilities. Brown and Stix [2014] focus on households’ deposits

and shows a connection with macroeconomic volatility and households’ experiences of a past

currency crisis. Their work however does not consider the determinants of other funding

sources such as interbank loans. This line of research contrasts the positions in foreign and

local currencies, but does not consider any heterogeneity across different foreign currencies.

Several contributions focus on lending specifically denominated in Swiss francs. Brown

et al. [2009] document substantial heterogeneity in the nature of Swiss franc loans across

countries. Yesin [2013] relies on the same dataset as we to illustrate and analyze the preva-

lent mismatch between assets and liabilities denominated in Swiss francs on European bank

balance sheets. Auer et al. [2012] focus on the refinancing of Swiss franc lending by Aus-

trian banks. They show a clear break during the crisis when funding through the unsecured

interbank market and bond issuance was replaced by funding through the repo market and

reliance on liquidity provision by central banks.

2

4

The second stream of the literature to which our work is related is the international

transmission of shocks through the activity of global banks, with several papers stressing

their central role in the crisis (Takats [2010], Avdjiev et al. [2012], McCauley et al. [2015],

Milesi-Ferretti and Tille [2011]). Cetorelli and Goldberg [2011] document the spreading of

shocks through cross-border lending and operations of local affiliates. Cetorelli and Goldberg

[2012] stress the relevance of banks’ internal capital markets as affiliates in more robust

countries can be used as sources of funds for the parent in a crisis. Cerutti et al. [2014]

assess the determinants of cross-border bank lending in a broad sample of countries. It finds

that the term premium in core economies matters, which captures the incentive for banks to

search for yield. Funding conditions of banks also play a role. Bruno and Shin [2014] find that

the global leveraging cycle in the banking sector is a prominent driver of international bank

capital flows. None of these contributions compare and identify differences across foreign

currencies.

Our work is also related to the literature on what drives non-bank actors to issue liabili-

ties in foreign currencies. Avdjiev et al. [2014] show the growing propensity by corporates in

emerging markets to issue debt in foreign countries. In addition to standard carry-trade con-

siderations, this reflects the ability of these firms to get around restrictions on capital mobility

(Caballero et al. [2015]). Hale and Spiegel [2012] show that the reduction in transaction costs

brought on by the euro led to a switch of corporate borrowing towards the euro. McBrady

and Schill [2007] find that the currency composition of borrowing by entities with no hedging

needs reflects the relative costs, proxied by deviations from covered and uncovered interest

parity.

A final stream of literature is the study of the consequences of currency mismatch on

the international transmission of shocks. This mismatch magnifies the adverse consequences

of sudden reversals in capital flows (Reinhart and Calvo [2000], Choi and Cook [2004]), for

instance leading to larger movements in international relative prices (Calvo et al. [2006]). Pri-

vate agents fail to take full account of this magnifying effect when incurring foreign liabilities,

leading to an inefficient amplification of the boom-bust cycle (Jeanne and Korinek [2013],

Mendoza [2010]).

3 Data and Stylized Facts

3.1 The Swiss Franc Lending Monitor

Following Yesin [2013], we rely on the Swiss franc lending monitor, a database maintained

by the Swiss National Bank using inputs from 20 participating central banks. Its purpose

is to provide information on the role of the Swiss franc in bank lending and funding across

a broad range of European countries. The data consist of quarterly observations on various

components of banks’ balance sheet positions starting at the latest in the first quarter of

3

5

2009. As data start earlier for some of the sample countries, we use an unbalanced sample

that starts in the first quarter of 2007 for our regressions.1 This allows us to cover at least

a small part of the the pre-financial crisis period as well. We present the stylized facts from

2009 only, to ensure comparability across countries.

We include 17 of the 20 European countries in our sample.2 The balance sheet items

are reported at the aggregate country level for all resident banks, including subsidiaries of

foreign banks but not foreign bank branches. The inclusion of subsidiaries of foreign banks

is important as they account for a very large market share, particularly in some Eastern

European countries.

Importantly for our purposes, the data provide a breakdown of balance sheet positions

across currencies.3 Specifically, all positions are divided between Swiss francs, all other foreign

currencies, and the domestic currency. This provides exceptionally detailed information on

balance sheet positions in the Swiss franc. While other foreign currency positions are not

broken down into individual currencies, we can estimate a breakdown across currencies based

on information from other sources. We find that the U.S. dollar dominates the non-Swiss

franc foreign currency positions in euro countries and advanced economies, and the euro

dominates the non-Swiss franc foreign currency position in the non-euro countries. There

are, in addition, smaller positions in yen and pounds in both country groups.

The data divide bank asset positions between lending and other assets, while liability po-

sitions are divided between deposits (including repo and interbank borrowing), own securities

issuance and other liabilities. Lending and deposits are further divided on counterparty types,

including resident households, resident non-financial corporations, resident banks (domestic

interbank), government, non-resident banks and non-resident non-banks.4 Our focus is on

lending from the domestic banking sector to the rest of the economy, so we exclude domes-

tic interbank positions. As the breakdown between households, non-financial corporations

and government is incomplete for many of the countries, we focus on the split between total

domestic non-bank, foreign bank and foreign non-bank positions.5

1The individual country charts in Appendix reflect the period covered for each country.2Austria, Bulgaria, Czech Republic, Croatia, Denmark, Estonia (Estonia is included twice, with the pre-2011sample included as a non-euro countries and the post-2011 sample included as a euro country), France, Ger-many, Greece, Hungary, Latvia, Luxembourg, Romania, Serbia, Slovenia, Slovakia, and the United Kingdom.Three countries, Italy, Poland and Iceland, are included in the data base, but not in our study. Italy is onlyincluded in some of the stylized facts looking at country averages, as the time variation in the data seemsimplausible and suggests data errors. Moreover, Poland is only included on the funding side, as Poland’s datacoverage of foreign lending and other assets is incomplete. Iceland is not included due to insufficient datacoverage.

3An advantage of using this data set over the BIS locational banking statistics for currency breakdown isthat it includes more European countries than the BIS reporting countries. It hence allows us to make moredetailed analysis of developments in foreign currency positions of European bank balance sheet.

4The data unfortunately does not divide positions with foreign bank counterparties on positions vis-a-vis aforeign parent bank and positions vis-a-vis an unrelated foreign bank.

5For the countries that do provide this split, the share of Swiss franc loans to domestic government is verysmall. We can hence consider non-bank lending to be lending to private non-bank residents.

4

6

3.2 Stylized facts

This section presents the main stylized facts for the different roles played by the Swiss franc

and by other foreign currencies in foreign currency lending. We contrast across sub-groups of

European countries when this is informative.

These stylized facts shows that not all foreign currencies are alike, as the patterns for

Swiss franc lending differ substantially from the pattern for other foreign currencies. This is

observed in terms of the prevalence of domestic vs. cross-border lending, the counterparties,

the evolution through time, and the funding of foreign currency lending positions.

3.2.1 Extent of lending in foreign currency

We first illustrate the relevance of foreign currency lending to non-bank residents. The left

panel of Figure 1 shows the shares of total bank lending that go to domestic non-bank residents

and are denominated in foreign currency. This form of lending accounts for a large share of

bank lending in emerging Europe. In contrast, it plays a much smaller role in countries in

the euro area and financial centers. While the euro and U.S. dollar play a dominant role, the

Swiss franc also matters. It has been the dominant foreign currency for domestic lending in

Austria, Hungary and Slovenia, and important in Greece, Romania, Serbia and Croatia on

the average for the sample period that we are considering.

0

10

20

30

40

50

60

70

80

90

IT SK LU EE2DE FR SI

CZ

GR

GB AT

DK

HU

BGRO LV R

SHR

EE1

Other foreign currencies

Swiss francs

(a) Foreign currency domestic lending to non-banks

0

10

20

30

40

50

60

70

80

90

IT SK LU EE2DE FR SI

CZ

GR

GB AT

DK

HU

BGRO LV R

SHR

EE1

Cross border lending in other foreign currencies

Cross border lending in Swiss francs

Cross border lending in local currency

(b) Total cross border lending

Figure 1: Foreign currency lending in percent of total lending.

Excluding domestic interbank lending. The charts are constructed such that if the bars of the two

charts are summed for each country, the remaining share of to 100 percent reflects domestic non-bank

lending in domestic currency. Averages across the quarters 2009Q1 to 2014Q4. EE1 refers to Estonia

prior to Q1 2011, and EE2 refers to Estonia after Q1 2011. Both figures are sorted according to the

share of foreign currency domestic non-bank lending in total non-bank lending. Source: SNB.

Foreign currencies play a different role in cross border lending (right panel of Figure

1). They account for a small share of such lending in emerging Europe, but a large share

in advanced economies, especially financial centers. The Swiss franc plays only a marginal

5

7

role in such cross-border lending. Austria, Graet Britain, Greece, Hungary and Luxembourg

are the only countries with non-negligible Swiss franc lending to foreign residents, a pattern

that likely reflects these countries’ roles in distributing Swiss franc funding to the remaining

countries in the sample.

3.2.2 Counterparties of lending in foreign currency

We next turn to the counterparties to whom banks lend in foreign currencies. Figure 2 splits

the lending to domestic non-bank residents between households and non-financial companies,

for loans in Swiss franc (panel (a)), other foreign currencies (panel (b)), and domestic currency

(panel (c)), for the countries that provide such a split. The Swiss franc is predominantly

used for lending to domestic households, reflecting the popularity of the Swiss franc for

denominating retail mortgages. Other foreign currencies are predominantly used for lending

to non-financial companies, which is likely to reflect a high share of trade and investment

credits for exporting and importing firms, mainly in euros and U.S. dollars. Finally, loans in

local currency are more balanced between households and firms.

Figure 3 shows the split of cross-border lending between loans to foreign banks and foreign

non-bank counterparties for the Swiss franc, other foreign currencies, and the local currency

of the lending country. We observe that foreign banks are the dominant counterparty for

most countries, and that this pattern is quite even across the various currencies. While loans

to non-banks account for a large and even dominant share for some countries, it is important

to note that overall cross-border lending is relatively small for these countries.

6

8

0

20

40

60

80

100

GB C

ZDK

DE LU IT SI

GR AT

RS

HU

BG HR

RO

EE2EE1

Share going to households

Share going to non-financial companies

(a) Swiss franc domestic lending

0

20

40

60

80

100

EE2GR C

ZGB

DE IT LU H

U SIBG R

S ATRO H

REE1

DK



(b) Domestic lending in other foreign currencies

0

20

40

60

80

100

SI IT RS AT

RO H

UHR

EE2GR

BG CZ LU EE1

DE

GB

DK



(c) Domestic lending in domestic currency

Figure 2: Foreign currency domestic lending: Sectoral shares

The data exclude domestic interbank lending. Averages across the quarters 2009Q1 to 2014Q4. France

and Slovakia are excluded due to lack of data. Moreover, Latvia is excluded in the Swiss franc figure

as it only provides the sectoral breakdown for other foreign currencies. EE1 refers to Estonia prior to

Q1 2011, and EE2 refers to Estonia after Q1 2011. Both figures are sorted according to the share of

Swiss franc lending to resident households. Source: SNB.

7

9

0

20

40

60

80

100

RS

HR

HU SI

LU BG ATFR IT D

EDK SK

GB

RO LV G

R CZ

EE1EE2

Share going to foreign banks

Share going to foreign non-banks

(a) Swiss franc cross border lending

0

20

40

60

80

100

HR

HU R

SDK

GB C

ZDE AT SI

LV SK FRGR LU R

O IT BGEE1

EE2



(b) Cross border lending in other foreign currencies

0

20

40

60

80

100

DK AT

GB

EE1FR D

E SK CZ LU IT H

R PLRO LV EE2

BGGR

HU R

S



(c) Cross border lending in domestic currency

Figure 3: Foreign currency cross border lending: Sectoral shares

Averages across the quarters 2009Q1 to 2014Q4. EE1 refers to Estonia prior to Q1 2011, and EE2

refers to Estonia after Q1 2011. Both figures are sorted according to the share of Swiss franc lending

to domestic households. Source: SNB.

8

10

3.2.3 Evolution of lending through time

We now turn to the evolution of foreign currency lending through time. The shares of the

various currencies present a substantial extent of heterogeneity.6 We summarize the pattern

by running panel regressions for the shares of the various currencies on time and country fixed

effects. In addition to running these regression for the overall sample, we also run them for

the sample of euro area countries, and the sample of other countries.7 The estimated time

fixed effects provide us with a summary measure of the development over time within each

subgroup.

The time fixed effects for the shares of the Swiss franc and other foreign currencies in

domestic lending are presented in Figure 4 (panel (a) and (b) respectively). The share of

Swiss franc lending has since been on a steady downwards trend since the financial crisis,

especially in countries that are not members of the euro area. Closer inspection of the data

shows that this trend has been most pronounced in the non-euro European countries which

have not been pegging to the euro during the sample period. By contrast, the share of other

foreign currencies have been much more volatile, and do not exhibit a particular downward

trend.

-4

-3

-2

-1

0

1

2

3

4

I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV

2009 2010 2011 2012 2013 2014

EURO Non-EURO Whole Sample

(a) Swiss francs

-4

-3

-2

-1

0

1

2

3

4


2009 2010 2011 2012 2013 2014


(b) Other foreign currencies

Figure 4: Time factor in foreign currency shares of domestic lending

Quarterly, 2009Q1 to 2014Q4. The data depicts the value of the time fixed effects estimated in panel

regressions of the share of lending to domestic residents in the respective foreign currency on time and

cross sectional fixed effects, for the respective subsample of countries. Time fixed effects are set to

zero in 2009Q1. Source: own estimations.

Figure 5 shows the results of a similar exercise for lending across borders. We observe a

similar pattern of reduction in the Swiss franc share since the crisis, with no such decrease in

the share of other currencies.6The Appendix provides figures for individual countries on the changes over time in the share of domesticlending that is denominated in Swiss francs and in other foreign currencies respectively

7We have additionally run these regressions for samples that split euro as well as non-euro countries furtherinto financial centers and periphery, and pegging and non-pegging non-euro countries. Results are availableupon request.

9

11

-4

-3

-2

-1

0

1

2

3

4


2009 2010 2011 2012 2013 2014


(a) Swiss francs

-4

-3

-2

-1

0

1

2

3

4


2009 2010 2011 2012 2013 2014


(b) Other foreign currencies

Figure 5: Time factor in foreign currency shares of cross border lending

Quarterly, 2009Q1 to 2014Q4. The data depicts the value of the time fixed effects estimated in panel

regressions of the share of lending to foreign residents in the respective foreign currency on time and

cross sectional fixed effects, for the respective subsample of countries. Time fixed effects are set to

zero in 2009Q1. Source: own estimations.

3.2.4 Funding of foreign currency lending

Our final stylized fact focuses on the mismatch between assets and liabilities in specific cur-

rencies. Anecdotal evidence suggests that banks have a variety of different funding models

for foreign currency lending. Residential mortgage loans in foreign currency are typically

extended in local currency, but indexed to the Swiss franc exchange rate, and subject to the

Swiss franc interest rate. Such loans typically to not require initial foreign currency funding,

but will give rise to a currency exposure by the extending bank, in turn giving rise to a need

for hedging. Other foreign currency loans are by contrast extended in Swiss francs directly,

when the borrower actually needs Swiss franc liquidity. Such loans will give rise to an initial

funding need by the extending bank.

Figure 6 shows that a large share of banks’ Swiss franc assets are not funded on balance

sheet, giving banks a net long position in Swiss francs. The situation is very different for

other foreign currencies where a larger share of loans is funded in the same currency. As

a results, the net positions are much smaller in these currencies for the vast majority of

countries. This pattern of net exposure was first documented by Yesin [2013]. This on-

balance sheet mismatch may reflect the high share of Swiss franc loans going to domestic

resident households, and possibly a different use of off-balance sheet hedging for such lending.

In Krogstrup and Tille [2016], we take a closer look at what drives European banks’ funding

needs in different currencies.

10

12

-80

-40

0

40

80

120

PLEE2

EE1DK SI

FR LU GB SK LV IT D

ERO H

R ATRS C

ZBG H

UGR

Swiss francs


(a) Swiss francs

Figure 6: Balance sheet currency mismatch across countries

Averages across the quarters 2009Q1 to 2014Q4 for foreign currency assets in excess of foreign currency

liabilities, in percent of foreign currency assets. The number reflects the percent of foreign currency

assets that are not funded on balance sheet. EE1 refers to Estonia prior to Q1 2011, and EE2 refers

to Estonia after Q1 2011. The figure is sorted according Swiss franc balance sheet mismatch. Source:

SNB.

4 Econometric Analysis of Foreign Currency Lending

4.1 Measures of financial flows

The domestic currency value of banks’ lending positions denominated in foreign currencies

can change for two reasons. First, exchange rate movements directly affect the value, with

an appreciation of the foreign currency raising the value of a foreign currency loans expressed

in domestic currency. We are not interested in such valuation effects, and instead focus on

the second reason, namely net new extension of loans in the currency of denomination. To

measure net new extension of loans, we adjust the data from the lending monitor to filter out

the direct valuation impact of exchange rate movements.

Consider the lending position of country c in a foreign currency j. We denote its value in

domestic currency at the end of period t by Lc,jt . We denote the exchange rate in terms of

units of local currency per unit of foreign currency as Sc,jt (so an increase is an appreciation

of the foreign currency). The total change in the value of the position between periods t− 1

and t consists of the capital flows F c,jt and the valuation impact of the exchange rate:

Lc,jt = Lc,j

t−1+ F c,j

t +dSc,j

t

Sc,jt−1

Lc,jt−1

Which we rewrite as:

lc,jt = f c,jt + Sc,j

t

where lc,jt = dLc,jt /Lc,j

t−1, f c,j

t = F c,jt /Lc,j

t−1and Sc,j

t = dSc,jt /Sc,j

t−1. There is one such relation

11

13

for positions in CHF and one for positions in other foreign currencies. While the Swiss franc

lending monitor does not provide the breakdown over the various currencies, data from other

sources show a dominant role of the euro for emerging European economies and the U.S.

dollar for the other countries.8 We thus assume that the positions in other foreign currencies

are denominated in one of these two currencies, depending on the countries group we consider.

4.2 Explanatory variables

We assess the drivers of lending flows by regressing f c,CHFt and f c,otherFX

t on a range of

variables capturing domestic and global conditions.

The first set of variables control for the characteristics of the domestic economy. Macroe-

conomic conditions are proxied by the domestic real GDP growth and CPI inflation. As

financial activity in foreign currencies is driven in part by international trade transactions,

we control for trade openness through the growth rate of total trade flows (exports plus im-

ports).9 We also include the change in lending in domestic currency to capture whether the

country is experiencing an overall credit boom, as opposed to changes in lending that are

heterogeneous across currencies.

The second set of variables reflects funding costs in the various currencies. We proxy them

by the spread between the money market interest rate in the local currency and the interest

rate in the Swiss franc (respectively euro, and U.S. dollar). A higher value indicates that

funding in the domestic currency is relatively expensive.

We next include the changes in the liability positions denominated in foreign currencies

(adjusted for the valuation effect of exchange rates) to see whether an increase in foreign

currency deposits or wholesale funding subsequently fuels lending in foreign currencies.

The fourth set of variables reflect exchange rate movements. We include the percent

appreciation of the Swiss franc (respectively euro, and U.S. dollar) vis--vis the domestic

currency. We also consider the volatility of exchange rate movements, which we compute as

the intra-quarter variance at a weekly frequency.

The fifth set of variables reflects the provision of liquidity by central banks in the major

currencies. We proxy it by the change in the ratio of monetary base to GDP.

Finally, we include the change in the VIX index to capture any impact of global risk

perceptions. We control for the fact that in mid-2013 the Swiss monetary base increased as

the financial service department of the postal administration was reclassified as a bank.

The descriptive statistics for all dependent and explanatory variables are listed in Table

8Specifically, we rely on three sources. The first is the ECB annual report on the international role of the euro(the latest of which is ECB [2014]). The second is information gathered from the web-sites of the nationalcentral banks. The third is a regression analysis, where we assume that exchange rate movements immediatelyaffect the local currency value of the positions denominated in foreign currencies, but affect outright flowsonly with a lag.

9Trade flows are taken in nominal terms, as financing needs by trading firms are driven by their nominaltransactions.

12

14

1. All variables are defined in relative changes (i.e. not percentages).

We also strive to control for the regulations that some countries enacted to restrict the

use of foreign currency loans out of concerns for financial stability purposes (IMF [2015]).

Note that our specification in first-difference indirectly controls for cross-country differences

in regulation that remained unchanged through time. Our focus is then on intra-country

changes in regulation during our sample. Controlling for such changes, which likely played

a significant role, is challenging as we lack a unified source of information.10 A specific

case is Hungary, which has taken the widest ranging measures in our sample. Specifically,

the Hungarian government introduced special repayment schemes and conditions for foreign

currency mortgages that strongly reduced their outstanding volume in the last quarter of

2011 and first quarter of 2012 (IMF [2013] box 2).11 We assess the effect of these measures

by including dummies for 2011Q4 and 2012Q1 for Hungary.

Mean Maximum Minimum Std. Dev. No. Obs

dlog(domestic lending CHF) -0.011 1.063 -0.568 0.138 458dlog(domestic lending OC) 0.004 0.605 -0.933 0.105 458dlog(cross border lending CHF) 0.090 10.967 -0.925 0.759 458dlog(cross border lending OC) 0.028 2.147 -0.715 0.215 458growth 0.007 0.127 -0.172 0.046 533inflation 0.031 0.162 -0.032 0.029 574dlog(gross trade) 0.009 0.234 -0.351 0.076 519dlog(lending in dom. currency) 0.012 2.285 -0.151 0.114 443idomestic − iCHF 0.026 0.177 0.000 0.032 544idomestic − iUSD 0.018 0.162 -0.032 0.032 544idomestic − iEUR 0.015 0.159 -0.029 0.031 544dlog(funding CHF) 0.025 3.221 -0.854 0.311 458dlog(funding OC) 0.006 0.387 -0.428 0.074 458CHF appreciation 0.011 0.170 -0.080 0.033 544USD appreciation 0.003 0.238 -0.096 0.050 544EUR appreciation 0.002 0.112 -0.051 0.018 544CHF volatility 0.028 1.428 0.000 0.075 544USD volatility 0.035 0.395 0.004 0.038 544EUR volatility 0.006 0.193 0.000 0.017 544d(Swiss M0/GDP) 0.018 0.165 -0.036 0.049 510d(US M0/GDP) 0.005 0.038 -0.006 0.009 527d(EU M0/GDP) 0.001 0.025 -0.021 0.011 510d(VIX) 0.000 0.033 -0.014 0.008 544

Table 1: Descriptive StatisticsfundingOC (CHF ) is funding in other foreign currencies (Swiss francs). Source: SNB.

As our database comprises a highly heterogeneous sample of countries, we undertake

separate regressions for each of four groups. The first group includes the countries in emerging

Europe, for which we take the euro to be the main foreign currency other than the Swiss franc.

10Even with that information, attributing values to the various changes in order to quantify their impact wouldbe difficult and beyond the scope of this paper

11In the last quarter of 2014, Hungary again enacted wide ranging regulations that required the forced conver-sion of large parts of its remaining outstanding foreign currency loans to domestic currency denomination.This measure however fall out of our sample.

13

15

The second group regroups advanced economies that are not members of the euro area. The

third group includes countries in the periphery of the euro area and the final group consists

of core euro area countries.12 For the last three groups, we take the U.S. dollar to be the

foreign currency other than the Swiss franc.

4.3 Interpretations of results: demand and supply factors

A study like ours faces two challenges for interpretation that are standard in the literature.

The first is the issue of reverse causality, as the dependent variable could cause the inde-

pendent ones. For instance, higher lending may boost GDP growth, or lead to inflationary

pressures. We address this issue in a standard (albeit imperfect) way by lagging the explana-

tory variables.13

A second, and more challenging, issue is to interpret the results in terms of demand and

supply factors. Higher lending volumes could reflect a supply push by foreign or local banks

as they attempt to invest additional funds, or a demand pull by borrowers who may want to

fund projects with improved prospects. A standard approach is to jointly analyze quantities

and prices to disentangle demand and supply factor, but we lack the pricing data to do so.

Instead, we can contrast the various drivers in terms of their likelihood of reflecting supply

or demand factors. Domestic growth and changes in trade flows are more likely to reflect

demand factors as a booming economy offers better return prospects in investment projects.

The spread across money market rates in foreign and domestic currencies can be interpreted as

supply factors, as the interest rates in USD, CHF and euro are not affected by the conditions

in the domestic country.14 Changes in the funding volumes in Swiss francs and other foreign

currencies (in terms of the component are orthogonal to other explanatory variables) are

unlikely to be driven by the demand from borrowers, and thus can be interpreted as supply

factors.

Developments in exchange rates, both in terms of levels and volatility, are harder to

interpret. Borrowing in an appreciating currency is of limited appeal for the lender, as it

raises the ultimate debt burden. While it should be more interesting for the lender, a bank

undergoing a careful risk assessment would rightly perceive a foreign currency loan as putting

more pressure on the borrower and thus entailing a larger risk of default.

Changes in the monetary base in Switzerland, the euro area, and the United States can

clearly be interpreted as supply factors as they are not affected by the situation in the do-

mestic economy. Similarly, movements in the VIX index are supply factors as they reflect the

situation in financial markets in advanced economies overall.

12The specific countries are as follows. Bulgaria, Czech Republic, Estonia, Latvia, Hungary, Russia, Croatiaand Romania for the first group; the U.K. and Denmark for the second group; Greece, Slovenia and Slovakiafor the euro periphery, and Germany, France, Luxembourg, Austria for the core euro area.

13The exception is the dummies for Hungary, but these do not constitute a concern.14This conjecture is more valid for the subsample of emerging economies than for advanced ones.

14

16

Therefore, even though we cannot rely on a price-quantity split to disentangle supply and

demand factors, several variables are more likely to reflect one of the two. Of course this

interpretation is somewhat conjectural and is to be taken with caution.

4.4 Drivers of domestic foreign currency lending

The regression results for net new Swiss franc lending to non-bank residents are presented

in Table 2. The first column presents the results for the entire sample, with the remaining

columns presenting the results for the various country sub-groups. As pointed out above,

domestic lending in foreign currency is highly heterogeneous, and most prevalent in emerging

economies and in the euro periphery countries. Our discussion thus focuses on these groups,

corresponding to the second and fourth specifications.

Our results show that domestic growth and inflation do not play a significant role. While

higher inflation is associated with more lending in Swiss francs overall, this results is not

robust to splitting the sample across various groups. Movements in international trade flows

matter for emerging Europe. A contraction in international trade reduces the lending in Swiss

francs, an effect likely driven by lending to firms engaged in trade.

The evolution in lending in domestic currency is not significant. This indicates that the

movements in Swiss franc lending do not simply parallel overall lending activity, controlling

for other drivers (which would imply a positive coefficient), but do not offset it either through

a reallocation between the franc and the domestic currency (which would lead to a negative

coefficient).

The differential in funding costs enters significantly, both overall and for emerging Europe

and the euro area periphery. Swiss franc lending is boosted by a lower interest rate in the

Swiss franc market, as well as higher interest rates in the euro and US Dollar markets (this

last aspect being also significant for advanced economies outside the euro area). Lending in

Swiss francs thus reacts to the relative cost of funding in Swiss francs and other currencies. By

contrast, lending is less responsive to new foreign currency funding. An exception is found in

emerging Europe where more funding in Swiss francs lead to higher lending in that currency.

Exchange rates matter, but in a heterogeneous way. An appreciation of the Swiss franc,

which makes loans in that currency more expensive, reduces the lending activity in that

currency in emerging Europe. Conversely, an appreciation of the euro boosts Swiss franc

lending in emerging Europe, as well as in non-euro area advanced economies and overall.

Exchange rate developments also have some impact through their volatility. Overall, Swiss

franc lending falls when the exchange rate vis-a-vis the Swiss franc and the dollar becomes

more volatile, and increases when the euro exchange rate fluctuates more. The effect is

however quite heterogeneous. Volatility plays no role in emerging Europe, and instead only

matters for advanced economies outside the euro area (where a higher volatility of the Swiss

franc exchange rate reduces lending) and in the euro periphery.

15

17

The provision of liquidity by the central banks of the foreign currencies plays only a

marginal role, and tends to have the wrong sign with more liquidity in Swiss francs followed

by a reduction in lending in emerging Europe. This suggests that our approach of lagging the

explanatory variables only partially addresses the issue of simultaneity, as the large increases

in liquidity took place during the crisis when lending contracted. Risk perceptions as proxied

by the Vix index do not matter.

Policy measures matter. The measures taken by the Hungarian authorities in late 2011

and early 2012 lead to a strong reduction of Swiss franc lending to residents in that country.

As pointed out below, there was a simultaneous increase in lending in other foreign currencies,

suggesting a substitution effect of measures that were primarily aimed at reducing Swiss franc

lending specifically.

The results for lending in other foreign currencies are presented in Table 3. Domestic

growth plays a partial role, and inflation does not matter. International trade flows are more

relevant, as lending in US Dollar in euro area countries is sensitive to international trade.

This suggests that the domestic lending in foreign currency in the euro area is geared towards

firms with international activities.

Funding costs play little role, in contrast to the role they play for Swiss franc lending. The

spread vis-a-vis the Swiss franc rate is significant for some groups, albeit with the wrong sign.

Funding in foreign currency matters, especially for emerging Europe where higher funding in

euros is associated with a subsequent increase in euro lending.

Also in contrast to their role in lending in Swiss francs, exchange rate movements in

terms of level (appreciation) and volatility do not play a clear role for lending in other foreign

currencies.

The liquidity provision by central banks do not have significant effects, with the exception

of dollar liquidity in emerging Europe, suggesting some substitution away from the euro as

dollar funding becomes more abundant. Risk perceptions are not associated with a clear

pattern of lending either.

As already pointed out above, the measures taken by Hungary to restrict Swiss franc

currency lending had an impact, with the first measures in late 2011 raising euro denominated

lending.

Overall, our results show a substantial heterogeneity in the drivers of lending across the

Swiss franc and other foreign currencies, and across countries. Swiss franc lending is most

sensitive to funding costs, funding availability, and exchange rate appreciations. The impact

of these variables is primarily observed in emerging Europe, and to a lesser extent in the euro

area periphery. We also observe a sensitivity to international trade, but only in emerging

Europe. The regulatory measures taken by Hungary strongly reduced Swiss franc lending to

domestic residents. By contrast, liquidity provision by central banks, and risk appetite do

16

18

Full Emerging Advanced Euro Eurosample Europe non-Euro periphery core

Growth 0.00 0.00 -0.27 0.37 0.68Inflation 0.52* 0.47 -2.59 0.52 -1.94dlog(gross trade) 0.14* 0.16* -0.25 0.06 0.20dlog(domestic currency lending) 0.09 0.14 -0.11 -0.05 0.43

idomestic − iCHF 5.29* 4.49** 6.54 6.29** 0.17idomestic − iUSD -1.71 -2.16* 5.94 -5.49*** 0.88idomestic − iEUR -3.62** -2.45* -20.5*

dlog(funding CHF) 0.01 0.08* -0.04 0.00 0.22dlog(funding OC) -0.11 0.14 0.05 -0.05 -0.68**

CHF appreciation -0.28 -0.53** -1.32 0.43 -0.08USD appreciation 0.00 0.08 -0.19 0.24 -0.20EUR appreciation 1.00** 1.04* 3.09**CHF volatility -0.31*** -0.01 -2.08** -0.14 -0.40USD volatility -0.40** -0.32 0.94 -0.92** -0.03EUR volatility 0.80* 0.29 1.95

d(Swiss M0/GDP) -0.16 -0.25*** -0.35 0.27 0.02d(US M0/GDP) 1.01* -0.09 -5.00 0.16 -1.57d(EU M0/GDP) 0.49 0.34 0.50 1.44 -0.27

d(VIX) -0.50 -0.66 3.14 -1.55 1.04

DHungary2011Q4 -0.04 -0.10***DHungary2012Q1 -0.14*** -0.08***

DPostfinance 0.00 -0.03*** -0.05 0.01 0.00

No. Obs 404 404 51 79 80No. cross sections 17 17 2 3 4R2 (R2-Adjusted) 0.22(0.14) 0.46(0.37) 0.36(-0.09) 0.51(0.35) 0.12(-0.16)

Table 2: Panel regression results for Swiss franc domestic lending flowsThe dependent variable is the valuation adjusted relative change across the quarter in lending to do-

mestic residents in Swiss francs. All explanatory variables are lagged one quarter. The four columns

lists the parameter estimates for different sub-samples of countries. fundingOC (CHF ) is funding

in other foreign currencies (Swiss francs). All regressions include fixed effects. */**/*** reflect sig-

nificance at the 10%/5%/1% levels, using white clustered standard errors. Dpostfinance is s dummy

capturing a structural break in the monetary base for Switzerland in Q3 2013.

17

19

not have a significant impact.15 Lending in other foreign currencies is associated with fewer

drivers than lending in Swiss francs. Specifically, trade flows matter for euro area countries,

whereas funding availability and policy restrictions have an impact in emerging Europe.

An interpretation of the results in terms of supply and demand factors, while somewhat

speculative as discussed in section 4.3, indicates a prominent role for both aspects in emerging

Europe. The relevance of interest rates and funding availability indicates that a more ample

supply of Swiss franc funding finds its way into lending. Policy measures that can restrict

the availability of lending also matter, with the measures taken by Hungary in 2011-2012

leading to a clear contraction in Swiss franc lending, with some offset in euro lending. The

sensitivity to trade flows is indicative of demand factors, while the interpretation of exchange

rate movements is more ambiguous. The impact of international trade for lending in other

foreign currencies in the euro area points to the relevance of demand factors.

4.5 Drivers of cross-border lending

We now turn to lending across borders. Table 4 shows the regression results for lending in

Swiss francs. As this form of lending is limited primarily to advanced economies, we focus

our discussion on the pattern in advanced economies, corresponding to the third and fifth

specifications respectively.

We find that only some explanatory variables matter, primarily in the forms of interna-

tional trade, funding costs and exchange rate considerations. Specifically, Swiss franc lending

is sensitive to international trade in the core euro area countries. There is some substitution

away from cross border lending in Swiss francs for non-euro area countries when the interest

rate in euro is low. An appreciation of the Swiss franc also matters for these countries, albeit

with an unexpected sign as lending increases when the Swiss franc appreciates. This may

reflect a need for the borrowing foreign banks to increase their Swiss franc funding when Swiss

franc positions increase due to valuation effects. Exchange rate volatility, liquidity provisions,

and risk perceptions have no significant impact.

The results for cross-border lending in other foreign currencies are presented in Table 5.

We again observe a role for international trade flows in the core euro area economies. Funding

costs play a role in advanced economies, albeit with an unexpected sign.

Exchange rate developments matter, with an appreciation of the Swiss franc boosting

lending in emerging Europe and non-euro advanced economies. Conversely, lending is reduced

when foreign currencies appreciate. Exchange rate volatility plays a marginal role, with a

reduction in lending by core euro area banks in periods of high volatility in the Swiss franc

exchange rate. This pattern could possibly reflect lending in foreign currency by banks in the

euro area to banks in emerging Europe, which in turn use this funding to extend lending in

15The absence of impact of liquidity provision could simply be due to the impact being fully captured throughinterest rates.

18

20

Full Emerging Advanced Euro Eurosample Europe non-euro periphery core

Growth 0.00 0.00 0.01 0.02 0.74*Inflation 0.34 0.14* -1.06 0.69 -0.40dlog(gross trade) 0.19** -0.04 -0.10 0.87 0.27*dlog(domestic currency lending) -0.11 -0.03 -0.38 0.33 -0.42

idomestic − iCHF 3.07*** 1.82 5.00*** -0.23 3.39**idomestic − iUSD -1.19 -1.20* -0.62 1.73 -2.39idomestic − iEUR -1.65 -0.98 -1.12

dlog(funding CHF) 0.01 0.00 0.01 0.01 0.03dlog(funding OC) 0.04 0.56* 0.00 -0.08 -0.29**

CHF appreciation -0.08 0.14 0.13 -1.15 -0.24USD appreciation 0.13 0.07 0.14 0.20 0.22EUR appreciation -1.15 -1.43 0.06CHF volatility -0.15 0.09 -0.45*** -0.60 -0.14USD volatility 0.11 0.29 -0.03 0.84 -0.09EUR volatility 0.25 -0.26 0.62

d(Swiss M0/GDP) -0.08 -0.07 -0.12 0.27 -0.04d(US M0/GDP) -1.09* -1.37** -1.37 -1.64 0.20d(EU M0/GDP) -0.07 -0.05 0.50 -0.14 -0.10

d(VIX) 1.07 0.79 3.27** 3.91 -2.10

DHungary2011Q4 0.08 0.07**DHungary2012Q1 -0.01 0.10

Dpostfinance -0.02 0.00 0.01 -0.03 -0.09***

Number of observations 404 194 51 79 80Number of cross sections 17 8 2 3 4R2 (R2-Adjusted) 0.23(0.14) 0.52(0.43) 0.63(0.37) 0.21(-0.04) 0.33(0.10)

Table 3: Panel regression results for other foreign currency domestic lending flowsThe dependent variable is the valuation adjusted relative change across the quarter in lending to do-

mestic residents in foreign currencies other than the Swiss franc, namely the euro for emerging Europe

and the U.S. dollar for the other groups. All explanatory variables are lagged one quarter. fundingOC

(CHF ) is funding in other foreign currencies (Swiss francs). The four columns lists the parameter

estimates for different sub-samples of countries. All regressions include fixed effects. */**/*** reflect

significance at the 10%/5%/1% levels, using white clustered standard errors. Dpostfinance is s dummy


19

21

Swiss franc. Higher risk perceptions also reduce cross-border lending by banks in core euro

area countries. Finally, Hungarian policy initiatives to reduce Swiss franc lending in late 2011

did not spill over into cross border lending.

Overall the results shows that our explanatory variables affect cross-border lending mostly

in foreign currencies other than the Swiss franc, which likely reflects the fact that this form

of lending is secondary for Swiss franc positions. International trade and exchange rate con-

siderations matter, albeit in a highly heterogeneous manner. In terms of supply and demand

factors, the role of international trade in cross-border lending in other foreign currencies by

core euro area banks can be read as a demand factor. The impact of the sensitivity to risk

relates more to supply consideration, while the interpretation of exchange rate volatility is

more ambiguous.

5 Conclusions

Using a novel database on lending in Swiss francs and other foreign currencies, we show that

banks’ use of foreign currencies for lending activities is highly heterogeneous. The Swiss franc

is to a high degree used for lending to domestic residents, whereas other foreign currencies are

used relatively more for lending across border. The Swiss franc is primarily used for mortgage

lending to domestic households, while domestic lending in other foreign currencies primarily

goes to firms. Finally, banks’ Swiss franc lending is not funded on balance sheet, in sharp

contrast to other foreign currency lending.

The various foreign currencies also show differentiated sensitivity to explanatory variables.

Swiss franc domestic lending is sensitive to funding costs, exchange rate developments, the

availability of funding, and to some extent international trade activity. Domestic lending in

other foreign currencies shows a more limited responsiveness to the factors we consider, but

lending across borders is more sensitive. Policy measures aimed at foreign currency lending

also matter, although the evidence is so far limited to the case of Hungary.

The overall message emerging from the analysis is that different currencies play very

different roles in bank balance sheets. There are no one size fits all patterns or policy responses

for containing negative side effects. Policies that aim to shield local economies from bank risk

taking and foreign shocks through banks’ international balance sheets should be tailored to

the specific circumstances of the country in question, and the roles that different currencies

play.

20

22


Growth 0.00 -0.03 0.10 1.15 -0.17Inflation 3.27 3.57 -5.85 -3.98 2.62dlog(gross trade) -0.63 -0.06 0.09 -3.97 0.39**dlog(domestic currency lending) -0.03 0.95 -1.66 -6.76 0.15

idomestic − iCHF 10.38 24.69 10.82 51.16 -3.74idomestic − iUSD -3.55 1.03 -1.13 -15.68 -2.13idomestic − iEUR -9.69 -32.41 -31.08*

dlog(funding CHF) -0.08 -0.27 0.05 -0.09 -0.11dlog(funding OC) -0.57 -1.96 0.60 -0.41 -0.02

CHF appreciation 0.43 -0.62 3.01** 6.82 0.21USD appreciation 0.18 -1.16 0.17 2.22 -0.40*EUR appreciation -0.68 2.27 -1.68CHF volatility -0.14 -0.89 -0.18 0.72 -0.25USD volatility -0.97 0.36 0.13 -9.87 -0.18EUR volatility 3.23 1.70 -7.99

d(Swiss M0/GDP) -0.85 -0.89 0.28 -1.80 -0.42*d(US M0/GDP) -0.88 -2.58 6.04 -5.10 1.64d(EU M0/GDP) 1.05 -0.36 2.58 3.36 1.42

d(VIX) -12.90* -20.10 -7.40 -15.02 -0.52

DHungary2011Q4 0.31 0.43DHungary2012Q1 0.09 -0.24

Dpostfinance -0.01 -0.11 0.43*** -0.16 -0.04

Number of observations 404 194 51 79 80Number of cross sections 17 8 2 3 4R2 (R2-Adjusted) 0.07(-0.02) 0.10(-0.05) 0.46(0.07) 0.16(-0.10) 0.42(0.22)

Table 4: Panel regression results for Swiss franc cross-border lending flowsThe dependent variable is the valuation adjusted relative change across the quarter in lending to foreign

residents in Swiss francs. All explanatory variables are lagged one quarter. fundingOC (CHF ) is

funding in other foreign currencies (Swiss francs). The four columns lists the parameter estimates for

different sub-samples of countries. All regressions include fixed effects. */**/*** reflect significance

at the 10%/5%/1% levels, using white clustered standard errors. Dpostfinance is s dummy capturing

a structural break in the monetary base for Switzerland in Q3 2013.

21

23


Growth 0.00 0.00 -0.05 1.02 0.47Inflation -0.06 -0.27 0.60 -0.03 0.67dlog(gross trade) -0.30 -0.53 0.49 0.02 0.32*dlog(domestic currency lending) -0.16 0.19 -0.28 -0.01 -0.12

idomestic − iCHF 4.34* 3.33 5.13** 3.01 3.76*idomestic − iUSD -2.62 -2.31 -5.09** -1.52 -3.92**idomestic − iEUR -2.09 -1.72 -3.05

dlog(funding CHF) 0.02 0.14 0.00 -0.04 0.13dlog(funding OC) 0.03 0.03 -0.23 0.13 -0.17

CHF appreciation 0.88** 1.24* 0.95** -0.16 -0.27USD appreciation -0.41* -0.92** 0.15 -0.15 0.07EUR appreciation 0.71 1.25 -0.83**CHF volatility -0.21* -0.21 -0.05 -0.35 -0.31**USD volatility -0.27 0.03 -0.71 0.13 0.38EUR volatility 0.68 0.06 -0.64

d(Swiss M0/GDP) 0.39** 0.02 0.18 1.40*** 0.38**d(US M0/GDP) -0.63 -0.74 1.61 1.23 -0.97d(EU M0/GDP) -1.93** -2.56 0.61 -2.07 -2.13***

d(VIX) -0.95 -0.31 -1.67 -3.01 -2.31**

DHungary2011Q4 -0.03 0.01DHungary2012Q1 -0.01 0.07

Dpostfinance -0.08*** -0.18*** 0.05* -0.05 -0.05

Number of observations 404 194 51 79 80Number of cross sections 17 8 2 3 4R2 (R2-Adjusted) 0.10(0.01) 0.13(-0.03) 0.48(0.11) 0.32(0.10) 0.28(0.04)

Table 5: Panel regression results for other foreign currency cross-border lending flowsThe dependent variable is the valuation adjusted relative change across the quarter in lending to foreign

residents in foreign currencies other than the Swiss franc, namely the euro for emerging Europe and

the U.S. dollar for the other groups. All explanatory variables are lagged one quarter. fundingOC

(CHF ) is funding in other foreign currencies (Swiss francs). The four columns lists the parameter

estimates for different sub-samples of countries. All regressions include fixed effects. */**/*** reflect

significance at the 10%/5%/1% levels, using white clustered standard errors. Dpostfinance is s dummy


22

24

References

Tobias Arian, Erkko Etula, and Tyler Muir. Financial intermediaries and the cross-section of

asset returns. forthcoming, The Journal of Finance, 2014.

Raphael Auer, Sebastien Kraenzlin, and David Liebeg. How do Austrian banks fund their

Swiss franc exposure? Austrian National Bank Financial stability report, pages 54–61,

2012.

Stefan Avdjiev, Zsolt Kuti, and Elod Takats. The euro area crisis and cross-border lending to

emerging markets. Bank for International Settlements quarterly review, pages 37–47, 2012.

Stefan Avdjiev, Michael Chui, and Hyun Song Shin. Non-financial corporations from emerging

market economies and capital flows. BIS Quarterly Review, December 2014.

Martin Brown and Ralph De Haas. Foreign banks in Emerging Europe. Economic Policy,

pages 57–98, 2012.

Martin Brown and Helmut Stix. The euroization of bank deposits in Eastern Europe. paper

presented at the 59th panel meeting of economic policy, 2014.

Martin Brown, Marcel Peter, and Simon Wehrmuller. Swiss franc lending in Europe. SNB

Mimeo, 2009.

Valentina Bruno and Hyun Song Shin. Cross-border banking and global liquidity. BISWorking

Papers 458, Bank for International Settlements, Aug 2014.

Julian Caballero, Ugo Panizza, and Andrew Powell. The second wave of global liquidity: Why

are firms acting like financial intermediaries? CEPR Discussion Papers 10926, C.E.P.R.

Discussion Papers, November 2015.

Guillermo A. Calvo, Alejandro Izquierdo, and Rudy Loo-Kung. Relative price volatility under

Sudden Stops: The relevance of balance sheet effects. Journal of International Economics,

69(1):231–254, June 2006.

Eugenio Cerutti, Stijn Claessens, and Lev Ratnovski. Global Liquidity and Drivers of Cross-

Border Bank Flows. IMF Working Papers 14/69, International Monetary Fund, April 2014.

Nicola Cetorelli and Linda Goldberg. Global banks and international shock transmission:

evidence from the crisis. International Monetary Fund Economic Review, 59:41–46, 2011.

Nicola Cetorelli and Linda Goldberg. Follow the money: Quantifying domestic effects of

foreign bank shocks in the Great Recession. American Economic Review Papers and Pro-

ceedings, 2012.

23

25

Woon Gyu Choi and David Cook. Liability dollarization and the bank balance sheet channel.

Journal of International Economics, 64(2):247–275, December 2004.

ECB. The international role of the euro. Technical report, The European Central Bank, 2014.

Galina B. Hale and Mark M. Spiegel. Currency composition of international bonds: The

EMU effect. Journal of International Economics, 88(1):134–149, 2012.

IMF. Hungary: Staff report for the 2013 article iv consultation and third post program

monitoring discussion. Staff report, IMF, March 2013.

IMF. Mind the credit gap. in regional economic issues for central, eastern, and southeastern

europe. Staff report, IMF, May 2015.

Olivier Jeanne and Anton Korinek. Macroprudential Regulation Versus Mopping Up After

the Crash. NBER Working Papers 18675, National Bureau of Economic Research, Inc,

January 2013.

Signe Krogstrup and Cedric Tille. What drives the funding currency mix of banks?

Manuscript, The Swiss National Bank, 2016.

Matthew R. McBrady and Michael J. Schill. Foreign currency-denominated borrowing in the

absence of operating incentives. Journal of Financial Economics, 86(1):145–177, October

2007.

Robert McCauley, Patrick McGuire, and Vladyslav Sushko. Global dollar credit: links to

US monetary policy and leverage. Working Paper 483, Bank for International Settlements,

January 2015.

Enrique G. Mendoza. Sudden Stops, Financial Crises, and Leverage. American Economic

Review, 100(5):1941–66, December 2010.

Gian-Maria Milesi-Ferretti and Cedric Tille. The great retrenchment: International capital

flows during the global financial crisis. Economic Policy, 66:285–330, 2011.

Carmen Reinhart and Guillermo Calvo. When Capital Inflows Come to a Sudden Stop:

Consequences and Policy Options. MPRA Paper 6982, University Library of Munich,

Germany, February 2000.

Elod Takats. Was it credit supply? Cross-border bank lending to emerging market economies

during the financial crisis. Bank for International Settlements Quarterly Review, pages

49–56, 2010.

Pinar Yesin. Foreign currency loans and systemic risk in Europe. Federal Reserve Bank of St

Louis Review, pages 219–235, 2013.

24

26

6 Appendix A: Data sources and definitions

• All balance sheet data for European countries are derived from the Swiss National

Bank’s Swiss franc lending monitor database.

• Valuation adjusted flows in bank balance sheet positions in different currencies are from

Krogstrup and Tille [2016].

• Nominal GDP: Quarterly, seasonally adjusted, quarterly values, not annualized. Source:

IFS.

• Real GDP: Index, 2005=100, seasonally adjusted. Source: IFS.

• Growth is defined as the quarter on quarter annualized percentage change in real GDP.

• Consumer price index. Source: IFS.

• Inflation is defined as the quarter on quarter annualized percentage change in the CPI.

• 3-month money market interest rates: Average of daily dates across the quarter. For

euro countries, euribor. Sources: Swiss National Bank and Datastream.

• Exchange rates. Average of daily rates over the quarter. Vis-a-vis the euro: Local

currency per euro nominal exchange rate. Includes the euro exchange rates for euro

countries, relating to their pre-euro currency. Vis-a-vis the USD: Local pre-euro cur-

rency per USD. Vis-a-vis the CHF: Local currency per Swiss franc. For euro countries,

the euro Swiss franc exchange rate has been used. Source: Datastream.

• Exchange rate volatilities are computed as the quarterly average of the daily squared

change in the log of the exchange rate.

• US monetary Base. Adjusted for reserve requirement changes. Quarterly average of

monthly levels. Source: St Louis Federal Reserve. In millions USD.

• Euro area monetary base: Quarterly average of monthly levels. Source: BIS. In millions

euro.

• Swiss monetary base: Quarterly average of monthly levels. Source: SNB. In millions of

Swiss francs.

• Federal Reserve bilateral USD currency swap volumes. Source: Federal Reserve. Quar-

terly averages, in millions of USD.

• SNB bilateral Swiss franc currency swap volumes. Source: SNB. Quarterly averages, in

millions of Swiss francs.

25

27

• VIX: Options based expected stock price volatility, based on the S&P, calculated by the

CBOE. Source: Datastream.

• Leverage of US securities brokers and dealers: As defined in Arian et al. [2014], page 9.

Source of total assets and liabilities of securities brokers and dealers: US Financial Ac-

counts (http://www.federalreserve.gov/datadownload/Build.aspx?rel=Z1). Quarterly,

based on end-of-quarter accounts.

• Exports and imports of goods and services: Quarterly, nominal, not seasonally adjusted.

Source: IFS.

7 Appendix B: Country specific figures

0

2

4

6

8

10

12

14

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Austria

0

2

4

6

8

10

12

14

16

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(b) France

0

2

4

6

8

10

12

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(c) Germany

0

5

10

15

20

25

30

35

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(d) Luxembourg

Figure 7: Euro countries financial centers: Foreign currency denominated assets

in percent of total assets.

Source: SNB.

26

28

0

2

4

6

8

10

12

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Greece

0

2

4

6

8

10

12

14

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(b) Italy

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(c) Slovakia

0

1

2

3

4

5

6

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(d) Slovenia

Figure 8: Euro countries non-financial centers: Foreign currency denominated

assets in percent of total assets.

Source: SNB.

0

10

20

30

40

50

60

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Great Britain

Figure 9: Non-euro countries financial centers: Foreign currency denominated

assets in percent of total assets.

Source: SNB.

27

29

0

10

20

30

40

50

60

70

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Bulgaria

0

4

8

12

16

20

24

28

32

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(b) Denmark

0

10

20

30

40

50

60

70

80

90

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(c) Estonia

0

10

20

30

40

50

60

70

80

90

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(d) Latvia

Figure 10: Non-euro countries non-financial centers, pegs: Foreign currency de-

nominated assets in percent of total assets.

Source: SNB.

28

30

0

5

10

15

20

25

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Czech Republic

0

10

20

30

40

50

60

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(b) Croatia

0

5

10

15

20

25

30

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(c) Hungary

-1

0

1

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(d) Poland

0

10

20

30

40

50

60

70

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(e) Serbia

0

10

20

30

40

50

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(f) Romania

Figure 11: Non-euro countries non-financial centers, no pegs: Foreign currency

denominated assets in percent of total assets.

Source: SNB.

29

31

0

2

4

6

8

10

12

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Austria

0

4

8

12

16

20

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(b) France

0

2

4

6

8

10

12

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(c) Germany

0

4

8

12

16

20

24

28

32

36

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(d) Luxembourg

Figure 12: Euro countries financial centers: Foreign currency denominated liabili-

ties in percent of total liabilities.

Source: SNB.

30

32

0

2

4

6

8

10

12

14

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Greece

0

2

4

6

8

10

12

14

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(b) Italy

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2

3.6

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(c) Slovakia

0

1

2

3

4

5

6

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(d) Slovenia

Figure 13: Euro countries non-financial centers: Foreign currency denominated

liabilities in percent of total liabilities.

Source: SNB.

0

10

20

30

40

50

60

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Great Britain

Figure 14: Non-euro countries financial centers: Foreign currency denominated

liabilities in percent of total liabilities.

Source: SNB.

31

33

0

10

20

30

40

50

60

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Bulgaria

0

10

20

30

40

50

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(b) Denmark

0

10

20

30

40

50

60

70

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(c) Estonia

0

10

20

30

40

50

60

70

80

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(d) Latvia

Figure 15: Non-euro countries non-financial centers, pegs: Foreign currency de-

nominated liabilities in percent of total liabilities.

Source: SNB.

32

34

0

4

8

12

16

20

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(a) Czech Republic

0

10

20

30

40

50

60

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(b) Croatia

0

10

20

30

40

50

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(c) Hungary

0

4

8

12

16

20

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(d) Poland

0

10

20

30

40

50

60

70

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(e) Serbia

0

10

20

30

40

50

2007 2008 2009 2010 2011 2012 2013 2014

Swiss francs


(f) Romania

Figure 16: Non-euro countries non-financial centers, no pegs: Foreign currency

denominated liabilities in percent of total liabilities.

Source: SNB.

33

From 2015, this publication series will be renamed SNB Working Papers. All SNB Working Papers are available for download at: www.snb.ch, Research Subscriptions or individual issues can be ordered at: Swiss National Bank Library P.O. Box CH-8022 Zurich Phone: +41 58 631 11 50Fax: +41 58 631 50 48 E-mail: [email protected]

2016-7 SigneKrogstrupandCédricTille:Ontherolesof differentforeigncurrenciesinEuropeanbanklending.

2016-6 PascalTowbinandSebastianWeber:Priceexpectations and the US housing boom.

2016-5 RaphaelA.AuerandCédricTille:Thebankingsector andtheSwissfinancialaccountduringthefinancialand European debt crises.

2016-4 ChristianHepenstrickandMassimilianoMarcellino: ForecastingwithLargeUnbalancedDatasets:The Mixed-FrequencyThree-PassRegressionFilter.

2016-3 AlainGalli:Howreliablearecointegration-based estimatesforwealtheffectsonconsumption?Evidence from Switzerland.

2016-2 PinarYeşin:ExchangeRatePredictabilityandState-of- the-ArtModels.

2016-1 SandraHanslinandRolfScheufele:ForeignPMIs: Areliableindicatorforexports?

2015-13 ThomasNellen:Collateralisedliquidity,two-parttariff and settlement coordination.

2015-12 JacobGyntelberg,MicoLoretanandTientipSubhanij: Privateinformation,capitalflows,andexchangerates.

2015-11 PhilipSauré:Time-intensiveR&Dandunbalancedtrade.

2015-10 NikolaMirkovandAndreasSteinhauer:BenBernanke vs.JanetYellen:Exploringthe(a)symmetryofindividual andaggregateinflationexpectations.

2015-9 AleksanderBerentsen,SébastienKraenzlinand BenjaminMüller:ExitStrategiesandTradeDynamics inRepoMarkets.

2015-8 ThomasNitschka:Isthereatoo-big-to-faildiscountin excessreturnsonGermanbanks‘stocks?

2015-7 AlinMariusAndries,AndreasM.Fischerand PinarYeşin:Theimpactofinternationalswaplineson stock returns of banks in emerging markets.

2015-6 JensH.E.ChristensenandSigneKrogstrup: TransmissionofQuantitativeEasing:TheRoleof Central Bank Reserves.

2015-5 PetraGerlach-KristenandSeánLyons:Mortgage arrearsinEurope:Theimpactofmonetaryand macroprudential policies.

2015-4 RetoFoellmi,SandraHanslinandAndreasKohler: A dynamic North-South model of demand-induced product cycles.

2015-3 KatarinaJuseliusandKatrinAssenmacher:Real exchangeratepersistence:ThecaseoftheSwiss franc-US dollar rate.

2015-2 LucasMarcFuhrer,BasilGuggenheimandSilvio Schumacher: Re-use of collateral in the repo market.

2015-1 PinarYeşin:CapitalflowwavestoandfromSwitzerland beforeandafterthefinancialcrisis.

Recent SNB Working Papers

On the roles of different foreign currencies in European ... · on contrasting foreign currency use...

Documents

Transcript of On the roles of different foreign currencies in European ... · on contrasting foreign currency use...